Soil Themes > Soil Erosion > Soil Erodibility in Europe (using LUCAS point survey data)
K-Factor: Background information
The greatest obstacle to soil erosion modelling at larger spatial scales is the lack of data on soil characteristics. One key parameter for modelling soil erosion is the soil erodibility, expressed as the K-factor in the widely used soil erosion model, the Universal Soil Loss Equation (USLE) and its revised version (RUSLE). The K-factor, which expresses the susceptibility of a soil to erode, is related to soil properties such as organic matter content, soil texture, soil structure and permeability. With the Land Use/Cover Area frame Survey (LUCAS) soil survey in 2009 a pan-European soil dataset is available for the first time, consisting of around 20,000 points across 25 Member States of the European Union.
The high-resolution soil erodibility map (500m) version 2014 incorporates certain improvements over the coarse-resolution map (10km) version 2011:
- High resolution dataset (500m) and application of Cubist regression-interpolation (better spatial accuracy)
- Soil structure was for the first time included in the K-factor estimation
- Coarse fragments were taken into account for the better estimation of soil permeability
- Surface stone content, which acts as protection against soil erosion was for the first time included in the K-factor estimation. This correction is of great interest for the Mediterranean countries where stoniness is an important regulating parameter of soil erosion
- The estimated soil erodibility dataset is verified against local, regional and national data found in the literature (21 Studies)
- Cyprus and Malta have been included in the analysis
K-factor High-resolution dataset (500m) - Version 2014
The aim of this study is the generation of a harmonised high-resolution soil erodibility map (with a grid cell size of 500 m) for the 25 EU Member States. Soil erodibility was calculated
for the LUCAS survey points using the nomograph of Wischmeier and Smith (1978). A Cubist regression model was applied to correlate spatial data such as latitude, longitude, remotely sensed and terrain features
in order to develop a high-resolution soil erodibility map. The mean K-factor for Europe was estimated at 0.032 t ha h ha-1 MJ-1 mm-1 with a standard deviation of 0.009 t ha h ha-1 MJ-1 mm-1. The yielded soil
erodibility dataset compared well with the published local and regional soil erodibility data. However, the incorporation of the protective effect of surface stone cover, which is usually not considered for the soil erodibility
calculations, resulted in an average 15% decrease of the K-factor. The exclusion of this effect in K-factor calculations is likely to result in an overestimation of soil erosion, particularly for the Mediterranean countries, where
highest percentages of surface stone cover were observed.
The soil erodibility dataset overcomes the problems of limited data availability for K-factor assessment and presents a high quality resource for modellers who aim at soil erosion estimation on local/regional, national or European scale. The new proposed dataset has also been verified against local/regional/national studies with very good results. Soil erosion modellers (and not only) may use it for their applications at any scale.
Title: Soil Erodibility in Europe High Resolution dataset (500m)
Description: This map provides a complete picture of the soil erodibility in the European Union member states. It is derived from the LUCAS 2009 point survey exercise and the European Soil Database.
Spatial coverage: 25 Member States of the European Union where data available (All EU member states except BG, RO and HR).
Pixel size: 500m
Projection: ETRS89 Lambert Azimuthal Equal Area
Temporal coverage: 2014
Input data source: LUCAS point data, European Soil Database
The Soil Erodibility Dataset is in Raster format. The public user can download 3 different datasets: a) Soil erodibility in Europe (K-factor), b) Soil Erodibility incorporating Stoniness (Kst Factor) and c) the Effect of Stoniness in K-factor (% reduction).
To get access to the data, please compile the online form; instructions will then follow how to download the data .
Fig. 1: K-factor high resolution(2014)
|Fig. 2: K-factor incrorporating Stoniness||Fig. 3: Effect of Stoniness in K-factor (% reduction)|
A complete description of the methodogoly (High resolution - 2014 version) and the application in Europe is described in the paper:
Panagos, P., Meusburger, K., Ballabio, C., Borrelli, P., Alewell, C.
Soil erodibility in Europe: A high-resolution dataset based on LUCAS, Science of Total Environment, 479–480 (2014) pp. 189–200
Download the article (Open Access): 10.1016/j.scitotenv.2014.02.010
K-factor coarse-resolution dataset (10Km) - Version 2011
In 2011, it was made available the Soil Erodibility (K-factor) dataset at a coarse resolution of 10km. The dataset was based on the LUCAS 2009 survey using a simple interpolation approach. This was a highly requested dataset by modellers but the resolution was quite coarse for regional applications. That is why we have developed the 2014 dataset incorporating many new innovations listed above. However, the coarse resolution (10km) dataset is also available for download.
The description of the methodogoly (Coarse resolution - 2011 version) and the application in Europe is described in the paper: Panagos, P., Meusburger, K., Alewell, C., Montanarella, L.
Soil erodibility estimation using LUCAS point survey data of Europe, Environmental Modelling & Software, Volume 30, April 2012, Pages 143-145, doi:10.1016/j.envsoft.2011.11.002
However, users are advised to use the latest (2014) high resolution dataset (and publication in 10.1016/j.scitotenv.2014.02.010).
|Important legal notice
© European Communities, 1995-
| European Commission - Joint
Institute for Environment and Sustainability
Marc Van Liedekerke(tel. +39-0332-785179)
Panos Panagos (tel. +39-0332-785574)